We are seeking a highly experienced and technically strong leader to head our Data & AI Engineering function. This role will be responsible for driving the technical vision, delivery excellence, and AI-first transformation across our data engineering and analytics teams.

The ideal candidate will bring a hands-on leadership approach, combining deep expertise in data platforms and applied AI with the ability to guide teams, architect scalable solutions, and deliver measurable business outcomes.

Role Summary:

This position requires a strategic yet hands-on leader who can operate across data engineering, analytics, and AI, and drive the organization toward becoming a truly AI-native delivery function. The role demands a balance of technical depth, leadership capability, and business acumen to deliver impactful, scalable, and future-ready solutions.

Key Responsibilities:

- Define and implement the AI-first engineering strategy, including standards, frameworks, and best practices across all engagements

- Lead, mentor, and scale a cross-functional team of data engineers, analysts, and integration specialists

- Drive adoption of AI-assisted development tools (e.g., Cursor, Claude Code, GitHub Copilot) as an integral part of the engineering workflow

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Design and deliver advanced AI solutions, including:

- LLM integrations ( Large Language Model)

- Prompt engineering frameworks

- Agentic workflows

- RAG-based architectures

- Architect and oversee end-to-end data solutions, including cloud data platforms, ERP integrations, and reporting systems

- Act as the technical authority, providing hands-on guidance through solution design, code reviews, and engineering best practices

- Collaborate with internal stakeholders and clients to identify opportunities for AI-driven optimization and automation

- Establish and enforce data governance, quality standards, and responsible AI practices.

Required Experience





- 10+ years of experience in data engineering, analytics, or data platform development

- Minimum 5 years of hands-on experience in applied AI/ML, including LLMs and modern AI frameworks

- Proven, day-to-day experience with AI-assisted development tools (such as Cursor, Claude Code, GitHub Copilot)

- Demonstrated success in leading technical teams within consulting or managed services environments

- Strong ability to translate technical solutions into business value for stakeholders.

Mandatory Key Skills

Core Technical Skills

- Strong proficiency in Python and SQL (including stored procedures)

- Hands-on experience with cloud data platforms (Azure, Snowflake, Databricks)

- Expertise in building and managing ETL/ELT pipelines

- Experience with business intelligence tools (Power BI, Tableau, Looker)

AI & Advanced Capabilities

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Deep understanding of:

- Large Language Models (LLMs)

- Prompt engineering techniques

- RAG (Retrieval-Augmented Generation) architectures

- Agentic AI frameworks

- Experience designing and deploying production-grade AI solutions

- Regular usage of AI-assisted development tools in coding and delivery workflows

Leadership & Stakeholder Skills

- Proven experience in team leadership, mentoring, and capability building

- Strong architecture and code review expertise

- Ability to communicate effectively with both technical and non-technical stakeholders

Business & Consulting Orientation





- Strong problem-solving skills with the ability to convert business requirements into scalable technical solutions

- Experience in client-facing roles and consulting environments

- Ability to articulate business impact and ROI of data and AI initiatives

Preferred Qualifications (Good to Have)

- Experience with ERP platforms (SAP, Dynamics, Plex)

- Familiarity with workflow automation tools (e.g., n8n)

- Background in leading analytics consulting firms (e.g., Tiger Analytics, Fractal, Tredence)

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Contributions to open-source AI or data engineering projects.

below are the Mandatory skill sets

- Strong programming expertise in Python and SQL (including stored procedures)

- Hands-on experience in building and managing ETL/ELT data pipelines

- Experience with cloud data platforms (Azure, Snowflake, Databricks)

- Solid understanding of data architecture and end-to-end data engineering workflows

-

Proven hands-on experience with Applied AI, including:

- Large Language Models (LLMs)

- Prompt Engineering

- RAG (Retrieval-Augmented Generation) architectures

- Agentic AI / workflow frameworks

- Demonstrated experience in building and deploying AI solutions in production environments

-

Regular, hands-on usage of AI-assisted development tools such as:

- Cursor

- Claude Code

- GitHub Copilot

-

Experience in technical leadership, including:

- Leading/mentoring engineering teams

- Solution architecture and design

- Code reviews and technical governance

- Robust understanding of data + analytics ecosystem, including BI tools (Power BI, Tableau, or Looker)

- Experience working in client-facing or consulting environments

- Ability to translate business requirements into scalable technical solutions

- Strong communication and stakeholder management skills, including explaining technical concepts to non-technical audiences

📌 Director of Data & AI Engineering (India)
🏢 Leading
📍 India